Comparative Evaluation of Bruker Biotyper and ASTA MicroIDSys for Species Identification in a Clinical Microbiology Laboratory

Abstract

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) has been widely used for microbial identification, because of its speed and accuracy, since its introduction to clinical microbiology laboratories. In this study, we evaluated the performance of ASTA MicroIDSys, a newly developed MALDI–TOF, and compared it with the widely used Bruker Biotyper. Microbial identification with the Bruker Biotyper system was performed by using a direct smear method and the Bruker Biotyper database (reference library version 6.0.0.0). The isolates were also tested in parallel, using the ASTA MicroIDSys system with a direct smear method and the MicroIDSys database, CoreDB v1.26. A total of 914 clinical isolates were recovered from the clinical specimens. Identical results with confidence scores (≥2.0, for the Bruker Biotyper) and acceptable scores (≥140 for the ASTA MicroIDSys) were obtained for 840 (91.9%) isolates. The minor errors were defined as misidentification at the species level, and the rate was 1.1% (9/792) for Bruker Biotyper and 1.6% (13/792) for ASTA MicroIDSys. Major errors were defined as misidentification at the genus level, and the rate was 0.3% (2/792) for both Bruker Biotyper and ASTA MicroIDSys. ASTA MicroIDSys showed reliable performance for microbial identification, which was comparable to that of the Bruker Biotyper. Therefore, ASTA MicroIDSys can be applied for the identification of microorganisms in clinical microbiology laboratories.

MALDI-TOF MS: A Reliable Tool in the Real Life of the Clinical Microbiology Laboratory

“…The computer software associated with the machine MALDI Biotyper (Bruker Daltonics GmbH, Bremen, Germany) uses this “score”; a score value of 2.0 is considered a reliable criterion of bacterial species identification, although the spectra obtained from a single strain are not identical in repeated runs because of a method-inherent noise. Score values between 1.7 and 2.0 are considered reliable for genus identification [ 22 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 32 ]. The machine MALDI VITEK MS (bio-Mérieux, Mercy L’Étoile, France) produces a confidence value, which can be reported as a percentage up to 99.9%.…”

“…Globally, the Microflex Biotyper (Bruker Daltonics GmbH, Bremen, Germany) and VITEK MS (bioMérieux, Marcy l’Etoile, France) are the commercially available MALDI–TOF MS systems currently implemented in clinical microbiology laboratories [ 28 , 29 , 30 , 31 , 32 ]. Recently, a new MALDI–TOF MS system, ASTA MicroIDSys (ASTA Inc., Suwon, Korea), was developed for the identification of clinically important microorganisms, producing discrepant results in the identification of microorganisms not frequently isolated in clinical laboratories, such as Paenibacillus spp.…”

“…and Weissella spp. Using ASTA MicroIDSys software (version 1.27), the species identification cut-off score of 130.0 is comparable to the score of 1.7 in Biotyper, according to a report comparing the two devices [ 3 , 5 , 25 , 29 , 30 , 31 ]. However, the ASTA MicroIDSys does not yet have the same distribution as those of Biotyper and VITEK MS, and its evaluation by the users is not comparable to the previous ones.…”

“…The results of MALDI-TOF MS are available in less than 1 min for only one sample and in less than 1 h if a target plate with 96 samples is used. The target plates are usually reusable after a simple cleansing procedure or are disposable according to the manufacturer’s instructions (Bruker Daltonics GmbH, Bremen, Germany, or MALDI Biotyper, bioMériex, Marcy l’Etoile, France, respectively) [ 28 , 29 , 31 ].…”

Rapid identification of bacteria from agricultural environment using MALDI-TOF MS

“…MALDI-TOF MS is mostly used for the identification of clinically relevant pathogens. It has been reported that this system can effectively identify bacteria even at species level from clinical samples (van Veen et al, 2010;Ponderand et al, 2020;Chung et al, 2021). However, it is increasingly utilised to detect foodborne pathogens in the complex food chain as well (Böhme et al, 2011;de Koster and Brul, 2016;Horváth et al, 2020).…”